Multiobjective design assessment and control law synthesis tuning for flight control development

Joos, H.-D.; Finsterwalder, R.

doi:10.1109/cacsd.1999.808687

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…In this sense, the trajectory optimization problem consists of transcribing the time-optimal control problem into a constrained parameter optimization problem and solving it with a direct approach using DLR's Trajectory Optimization Package 25) 'trajOpt,' that is included in the MOPS software environment [26][27][28] and implemented in MATLAB, 29) which solves multi-objective design problems that are mapped to weighted min-max optimization problems. MOPS is a versatile tool widely used in the aeronautical community [26][27][28][30][31][32][33][34] to support many aspects of general control design processes, such as multi-model and multi-case design problems, robust tuning via Monte-Carlo simulations, control law robustness assessment, worst-case analysis, and parameter estimation. A key advantage of using the trajectory optimization package trajOpt/MOPS, originally designed to solve hybrid multiphase trajectory optimization problems for launch vehicles, is that boundary conditions at the beginning and end of each phase of the desired maneuvers are considered in an efficient way.…”

Section: Time-optimal Slew Maneuver Problem Formulationmentioning

confidence: 99%

Fast Slew Maneuvers for the High-Torque-Wheels BIROS Satellite

2018

Trans. Japan Soc. Aero. S Sci.

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The satellite platform BIROS is the second technology demonstrator of DLR's 'FireBIRD' space mission aiming to provide infrared remote sensing for early fire detection. Among several mission goals and scientific experiments, to demonstrate a high-agility attitude control system, the platform is actuated with an extra array of three orthogonal 'High-Torque-Wheels.' However, to enable agile reorientation, a challenge arises from the fact that time-optimal slew maneuvers are, in general, not of the Euler-axis rotation type; especially whenever the actuators are constrained independently. Moreover, BIROS' on-board computer can only accommodate rotational acceleration commands twice per second. The objective is therefore to find a methodology to design fast slew maneuvers while considering a highly dynamic plant commanded by piecewise-constant sampled-time control inputs. This is achieved by considering a comprehensive analytical nonlinear model for spacecraft equipped with reaction wheels and transcribing a time-optimal control problem formulation into a multi-criteria optimization problem. Solutions are found with a direct approach using the trajectory optimization package 'trajOpt' of DLR-SR's optimization tool, Multi-Objective Parameter Synthesis (MOPS). Results based on numerical simulations are presented to illustrate this method.

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Section: Time-optimal Slew Maneuver Problem Formulationmentioning

confidence: 99%

Fast Slew Maneuvers for the High-Torque-Wheels BIROS Satellite

2018

Trans. Japan Soc. Aero. S Sci.

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“…Altematively, it may be formulated by maximizing the relative stability of eigenvalues as denoted by ^, ./^y^^ =minrRe(e/g. )/|e/g.|j, or by minimizing the absolute stability of eigenvalues given as q^^^.^i^te ~ ^^^ [^^(^^Si)] (Joos and Finsterwalder 1999).…”

Section: Stabilitymentioning

confidence: 99%

Multiobjective Evolutionary Algorithms and Applications

Tan¹,

Lee²,

k-c-tan³

et al. 2005

Advanced Information and Knowledge Processing

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Performance-based control system design automation via evolutionary computing

Tan

2001

Engineering Applications of Artificial Intelligence

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--This paper develops a parallel evolutionary algorithm based design unification of linear control systems in both the time and the frequency domains under performance satisfactions. A speedup of near-linear pipelinability is observed for the parallelism implemented on a network of transputers of Parsytec SuperCluster. The approach is capable of tackling practical constraints such as actuator saturation or transportation delays, and can be automated by efficient evolution from plant step response data, bypassing the system identification or linearization stage. Intelligently guided by the evolutionary optimization, control engineers are able to obtain an optimal "off-the-computer" controller by feeding the developed CACSD system with plant I/O data and customer specifications, without the need of formulating a differentiable performance index or linearly parameterization.Validation results against linear and nonlinear physical plants are convincing, with excellent closedloop responses and good robustness in the presence of practical constraints and perturbations.2

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Multiobjective design assessment and control law synthesis tuning for flight control development

Cited by 3 publications

References 9 publications

Fast Slew Maneuvers for the High-Torque-Wheels BIROS Satellite

Fast Slew Maneuvers for the High-Torque-Wheels BIROS Satellite

Multiobjective Evolutionary Algorithms and Applications

Performance-based control system design automation via evolutionary computing

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